Principal Machine Learning System Engineer

Atlassian is a company that focuses on unleashing the potential of every team through their software products. They are seeking a Principal Machine Learning System Engineer to set the technical direction for search infrastructure, driving outcomes across teams and functions while influencing peers and stakeholders.

Responsibilities:

• Define and champion the multi-year technical roadmap for search serving, vector infrastructure, and agentic retrieval
• Identify architectural inflection points — such as the evolution from keyword to semantic search, or the shift toward retrieval-for-agents — and build organizational consensus around the right path forward
• Drive high-impact initiatives across teams that do not report to you
• Influence peers, partner teams, and stakeholders by framing problems compellingly, co-authoring shared technical strategies, and creating forums — deep dives, design reviews, working groups — where the best ideas win on merit
• Navigate ambiguity and competing priorities across the Search Platform, ML Platform, AI Gateway, and Rovo product teams to keep critical cross-functional programs on track
• Own the technical strategy for retrieval systems that ground Rovo agents and AI workflows, including personalized indexes, multi-step retrieval pipelines, and RAG infrastructure at scale
• Anticipate how agentic use cases will stress existing search architecture and proactively design for those requirements before they become blockers
• Set the standard for production ML serving, cost discipline, and reliability across the search stack
• Drive FinOps-oriented decisions — such as vector cluster right-sizing and query embedding caching — that deliver material infrastructure savings without sacrificing SLO targets
• Raise the technical bar across the organization through code review, design feedback, and sponsoring the growth of senior engineers toward principal-level impact

Requirements:

• Set the technical direction for search infrastructure that powers Rovo, Jira, Confluence, and the broader Atlassian AI platform
• Define and champion the multi-year technical roadmap for search serving, vector infrastructure, and agentic retrieval
• Identify architectural inflection points — such as the evolution from keyword to semantic search, or the shift toward retrieval-for-agents
• Build organizational consensus around the right path forward
• Earn alignment through technical credibility, clear reasoning, and the ability to make complex tradeoffs legible to engineers, product managers, and senior leadership alike
• Drive high-impact initiatives across teams that do not report to you
• Influence peers, partner teams, and stakeholders by framing problems compellingly, co-authoring shared technical strategies, and creating forums — deep dives, design reviews, working groups — where the best ideas win on merit
• Navigate ambiguity and competing priorities across the Search Platform, ML Platform, AI Gateway, and Rovo product teams to keep critical cross-functional programs on track
• Own the technical strategy for retrieval systems that ground Rovo agents and AI workflows, including personalized indexes, multi-step retrieval pipelines, and RAG infrastructure at scale
• Anticipate how agentic use cases will stress existing search architecture and proactively design for those requirements before they become blockers
• Set the standard for production ML serving, cost discipline, and reliability across the search stack
• Drive FinOps-oriented decisions — such as vector cluster right-sizing and query embedding caching — that deliver material infrastructure savings without sacrificing SLO targets
• Raise the technical bar across the organization through code review, design feedback, and sponsoring the growth of senior engineers toward principal-level impact